> From this perspective, fields that require deep understanding, like math, require memory just as fields with a breadth of shallow knowledge do, though in different ways.
I'm interested in understanding how others use Anki for conceptual subjects like pure math or physics. I believe many fundamental rules in Spaced Repetition (e.g. like keeping cards concise) are thrown out the window for conceptual subjects.
Flashcards are brilliant. Anki is finally usable after they ditched the hot garbage algorithm they were using. Previously I've used the Leitner method and I stil think that's the best one for me.
Used to use Anki for foreign language learning. Guessing it would have been useful to memorise calc, chem and physics equations if it had existed when I was young.
I tried to make an auto flashcard generator but ran into the issue that one word can map to many senses. But most word frequency datasets don't disambiguate the sense. So if you want to include all the senses for a word while ranking words by frequency they all get the same starting position.
I use Anki to learn French, Chess openings/tactics/techniques, to unscramble letters for scrabble, for Pub Trivia... The options are kind of limitless.
As a mid-30s guy who has well passed the neuroplasticity of his teen years, it's a godsend for me.
To echo the author's thoughts though, I can't prove empirically that I learn more effectively using Anki (or spaced repetition) than other methods... Only anecdotally. I have a shockingly poor memory, but now I'm B2 certified in French and an ~1800 Elo on chess.com .
I do a really lightweight version of flash cards. Everytime I'm learning a new tool or tech, I grab oversized notecards (my favorite are 8x5" dot-grid cards). I put a label at the top, and create bullet points of each item i want to remember. I then review. No individual cards for each item or anything. Just all the things grouped on one card as bullet points.
For example, I'll have a `sqlite` card, and put all the commands and everything on it, as I learn them. I'll use it as a cheatsheet, but then also a few minutes of mindful review. This for the toolings that I want to know well enough to not get slowed down googling the commands. I do this for a lot of CLI tools, but also things I need to remember about the business of my company and working across group, etc....
Eventually the five or six working cards I have, get put on a pile and new ones come in.....
> prefer your own flashcards to other people’s flashcards, at least for fields that require deep understanding
For me, much of the value of flashcards comes in the making of them. Part of it is thinking about what each flashcard will say, and part of it is the action of writing it down in handwriting.
The best advice I've ever read about flash cards is if you are dreading to review, because you are forgetting your cards or they are too complicated, you are writing cards wrong. Learning is supposed to be fun! Also, Common Core should ship Anki decks. I seriously think so many problems with education stem from students not realizing that memorizing is actually very easy with FSRS, and thus struggling and hating learning.
> How do I actually use flashcards? My software of choice is Anki. I am not completely satisfied with it. The UI looks dated, the WYSIWYG HTML editor is clunky, and the undocumented file format makes potential porting and interoperability tricky.
And we still love it. I'm on the same page. This phenomena feels oddly satisfying.
My sense is the same as the authors that LLMs + an Anki-like -> mediocrity. But I feel like there ought to be such potential there! Even just things as simple as rewording the same question a bunch of equivalent ways to avoid recognizing the sentence structure...
Downside for AI potential as a whole, framed broadly: We don't seem to be good enough yet at identifying what friction is functional and what we should strive to automate/eliminate.
I once took a psychology course with my girlfriend at the time. She and her pals would be up all night studying with flashcards. I'd just walk into class, learn about it, never study, and get A's on the tests.
When they asked me how I was doing it I explained that I'm there to learn understand the topic and I don't give a damn about the test. So I just let my curiosity lead the way, it causes me to ask questions in and out of class, email the professor about them, do my own research and experiments. Despite not letting the test be my guide, this prepared me for the test anyhow.
I'm glad they work for some people, but flashcards to me seem like they provide a shallow kind of understanding. I don't want to remember the equation, I want to be able to derive it in a pinch, and flash cards don't give me that.
For language learning, I wish there was an audio-first flashcard app that changes up the example sentences every time. Right now, I'm using Anki to learn Japanese vocabulary from N5 to N3[1]. I know the words and the example sentences well enough to read N3-level text, provided I know the grammar. But when it comes to listening, I struggle to understand even N4-level spoken Japanese. Anki just doesn't offer enough variety for me to truly internalize what the sound means in different contexts. Plus, seeing the text before hearing the audio tricks my brain. I think I'm learning the sound, but it's an illusion because I already know the meaning from seeing the word first.
[1] I feel like Anki offers diminishing returns once you get past N3. Advanced words usually have subtle nuances that you can only really pick up through rich context, like in a full paragraph or a TV scene. Native-speaking kids can understand complex words in context because they have a deep grasp of a smaller, simpler vocabulary. That’s why I’m focusing on mastering high-frequency, simple words first to build a learning flywheel. I'm hoping this will eventually let me pick up new words naturally through reading and listening, just like a native kid does.
Audio first is an interesting idea. As a fluent speaker who's always felt ashamed of his poor writing skills that's actually something that I would want as well.
As for building a learning flywheel. I had a working prototype pre-AI Python project in notebook format that set the foundation for how I thought Kanji learning (or any complex interrelated domain) should build on SRS.
My premise is we should learn by associating what you know with what you should know, based on frequency across the language, not some arbitrary deck… And you shouldn't have to waste effort self reporting, the app should give you similar options to guess from, then if you're wrong, you're wrong.
> Some people also use LLMs to generate flashcards. And of course, the result will be those impersonal, mediocre cards.
> I won’t say LLMs are useless for this. But from my trials, I get about 1 card that’s useful to me out of 10, and even that 1 card still needs rewriting.
I don't know the specifics of how the author tried to do so, but from what I've seen the majority of attempts are, let me drop a chapter of a textbook and say "make flashcards." If that is what we are talking about, then yes, LLMs are useless.
In my mind, though, this is sort of like looking at the very first GitHub Copilot LLM autocomplete from a couple of years ago and concluding, yeah it's nice for one-liners, but it cannot write an app.
If you create a framework around your card-creation AI so that it can use tools, and verify its work to ensure common card-creation pitfalls don't happen, you can get pretty high-quality cards. In my experience, you go from a 10~20% hit rate to a ~90% hit rate, which in my mind is good enough. I got to ~75% quality just from a two extra LLM calls that would assess a potential card against a standard set of rules (adapted from [0]). There are huge Pareto gains to be had here.
I've generated thousdands of cards over the last few months this way. I let the AI add it directly to Anki via AnkiConnect. Then, if when I go to review I find a card that my AI created and I don't like it, I just delete it.
Removing the limitation of card creation is really quite compelling, and I think the area is still highly under-invested in. Would be cool to see a generic framework evolve that one could use. For now, I've been using a personal fork of clanki [1].
I used anki for learning japanese, and what I noticed while is that, at least for me the act of reviewing flashcards became a burden itself. It was not fun nor pleasant. I’d go back to using Anki if i’d know how to solve this.
> Most of my cards are handwritten by me and accommodate my brain.
I'm guessing from all the talk about Anki that people are missing this part. I think these frictionless, digital replacements for note cards are solving the wrong problem. You're never going to spend more time on a given flashcard, and better absorb the information on it, than the first time, when you're sitting there making the thing. Making this step as brief as possible is a bad idea.
When I was a kid I used flashcards to memorize the multiplication tables up to 12 and it allowed me to do very rapid mental math from that point on, and I still can to this day. It was useful for math quizzes and tests in school but it's also useful for life in general. Going up to 16 might be even better.
I use the Livio English Dictionary to look up words when I read on my tablet and I noticed one day that it keeps a search history, and I got an idea to make an Anki flashcard collection consisting of all the words I've needed to look up while reading. Despite being an obsessive reader my entire life I still regularly encounter words I'm not 100% certain about. Reading itself has spaced repetition built right in, assuming you quiz yourself and then follow up with a dictionary.
Aside: the example question ("What is the intuition that two reflections gives a rotation?") could have a more intuitive answer involving flipping an actual flashcard over twice, funnily enough...
I find using flashcards very stimulating, however to reach this status it took me quite some time and some trial and error. So if you're new at using flashcards don't quit just yet! Keep using them. My morning ritual is now coffee and anki.
Like the author said, understanding the card you're writing in your deck is fundamental. In my case, I would add, this is even true of when you add language cards. For example, I once added the word `thwart`. This card doesn't "cleanly" translate to my native tongue, and I was failing it at all times, I was confusing it with other words such as stifle, stymie etc because have a close meaning but not quite the one in thwart. Only after I grasped the exact definition and usage of it I started to not block on it anymore. I now attempt to be better at it by trying to also recall or make up the antonym of a certain word.
Also I started to create decks for:
1. Emacs commands, including custom shortcut which I use daily, or trying to drill new commands or features that I leant.
2. passages from books I read, mostly for those I use cloze deletions.
3. simple arithmetic, in order to be quicker at doing those without having to use a calculator at all times with me
4. shell commands, for example less frequently used git commands, grep or rg options.
A final note on using LLMs for flashcard creation. Sometimes the LLM can come up with some useful examples, or memory hooks, which help in retaining the information. Yes, I agree here with the author: out of 10 cards created with the LLM you're probably going to retain just one, and even that one will need rewriting.
Most people commenting here seem to be focusing on memorization, which seems to miss the main point of the article. The big insight here is the chunking part, not the memorization bit.
I use anki in a similar way to the author and it has been truly transformative to my learning and daily habits.
And, like the author, anki has become part of my daily workflow even for things that it's not really specifically designed for; e.g. easy frictionless LaTeX notetaking, cross-referenceable database (via note ids), incremental learning repo, long-term reminders (gtd-style) etc.
I've always loved and used flashcards, and relate to this article. I have built my own learning tool based on concept maps, which was inspired by Joseph D. Novak's book "Learning How to Learn". Concept maps are focused on how large networks of concepts connect to each other forming large graph spaces. One of the key problems after creating or encountering a very large map, though, is how to approach them in chunks. So I built a flashcard-inspired feature that chooses a concept at random and focuses your view on just that concept and its directly connected concepts. It's effectively a conceptual flashcard generator. You can check it out here:
https://thinkingtools.software/concepticon
It's a (sorry, Mac only at the moment) desktop app that uses plain text files in a format you can easily edit yourself in any text editor.
Two really good modern books on how we actual learn are.
1. The ABCs of How We Learn by Daniel L. Schwartz
2. How Learning Happens 2nd by Paul A. Kirschner & Carl Hendrick
I can really recommend them. Now back to flashcards and active recall. They are the secret sauce. People in the thread are saying that understanding is important, while I agree you should understand things its not THAT important.
Important is that you remember not only *facts* what something is. But also how to do something. If you stare at a blank page not being able to do something like writing a a simple typedef struct in C. But knowing what a typedef and struct is, you are missing procedural knowledge.
If you can only programming with an IDE giving you cues like autocompletion you will never form the memory for the actual symbol. Only when you active recall something it will be rememberd until it becomes automatic freeing your working memory from the load and reducing cognitive load overall.
I strongly believe that an AI rephrasing your backside and giving some additional knowledge from your own notes is helpful. You should still write your own notes and flashcards, an AI can help here too but just dont copy and paste them.
Learning can be so much, creating mental models and checking their validity, creating anecdotes, connecting new knowledge and ideas to already learned ones. Have fun!
There are many people that start using anki or flashcards only to stop doing them after a month.
Another interesting observation is that some people use flashcards to optimize for testing not learning. You can get good grades (really good ones) but it might hurt your actual learning. (What that actual means would be a longer topic)
Thank you for the recommendations! The 2 books seem to be a little more detailed than the average general-audience book but not too intense and deep like a textbook.
He makes some good points. Anki is indeed popular, so this is true too.
I am using my own set of flashcards via self-written computer programs,
mostly small scripts. The core is simple: one "side" has the question,
the other "side" has the answer. I enhanced this on the commandline though,
e. g. I can refer to local images (we can show this on the terminal, e. g.
I use KDE konsole and then some different commandline programs to show
things there. I can even show individual slides of .pdf pages via
https://github.com/hzeller/timg, which is pretty cool since I can control
which pdf file to show, sometimes manipulating them before showing that).
The author of that blog post at lesleylai, though, is wrong in some regards.
For instance:
> don’t memorize what you don’t understand
I totally understand what he means, e. g. "understand it first before memorizing",
and while this is in some ways true, in other ways it is not. I literally had to
memorize crap knowledge in order to pass some exams. Some of it was simply boring to no ends, other things were too complicated, but in BOTH cases, being able to memorize it, helped. I may not always understand everything, but being able to connect at the least some parts, did help, just like a spider web that is built up slowly. With that I could lateron learn more, connect more and so forth.
So, while I do agree that understanding is better, sometimes you can not, perhaps you lack time. Even in ALL these cases I had over the years, it still was better to be able to memorize even trivial facts. Of course eventually you have to be picky as to what knowledge you want to store in the brain, since I think it can not store infinite knowledge really (just about everyone forgets stuff eventually), but if your goal is to e. g. pass some exams quickly, then being able to quickly memorize even trivial crap, can be useful. There are a few other things I disagree with too, but for the most part I think this is a very useful blog entry. I am curious what people use else, e. g. other than anki and so forth. Or they may have other learning tricks. I always try to re-align my knowledge when it is for an important topic I care about; topics I once learned but never need again I kind of put into a "storage" preservation mode, e. g. if I ever need it again, I can look it up, but other than that I focus on what seems to be more important to me.
Just as a datapoint - I really like learning with Anki. If there was another method that would let me learn at 200% speed, I would pick Anki.
This is moot anyway, because most other learning methods require longer focus and are not possible to do while on the go, during short commute in a tram, or 3 minute wait in a queue, and much more.
32 comments
[ 4.0 ms ] story [ 70.3 ms ] threadI'm interested in understanding how others use Anki for conceptual subjects like pure math or physics. I believe many fundamental rules in Spaced Repetition (e.g. like keeping cards concise) are thrown out the window for conceptual subjects.
As a mid-30s guy who has well passed the neuroplasticity of his teen years, it's a godsend for me.
To echo the author's thoughts though, I can't prove empirically that I learn more effectively using Anki (or spaced repetition) than other methods... Only anecdotally. I have a shockingly poor memory, but now I'm B2 certified in French and an ~1800 Elo on chess.com .
Do I still forget things all the time? Yes.
For example, I'll have a `sqlite` card, and put all the commands and everything on it, as I learn them. I'll use it as a cheatsheet, but then also a few minutes of mindful review. This for the toolings that I want to know well enough to not get slowed down googling the commands. I do this for a lot of CLI tools, but also things I need to remember about the business of my company and working across group, etc....
Eventually the five or six working cards I have, get put on a pile and new ones come in.....
For me, much of the value of flashcards comes in the making of them. Part of it is thinking about what each flashcard will say, and part of it is the action of writing it down in handwriting.
And we still love it. I'm on the same page. This phenomena feels oddly satisfying.
Downside for AI potential as a whole, framed broadly: We don't seem to be good enough yet at identifying what friction is functional and what we should strive to automate/eliminate.
When they asked me how I was doing it I explained that I'm there to learn understand the topic and I don't give a damn about the test. So I just let my curiosity lead the way, it causes me to ask questions in and out of class, email the professor about them, do my own research and experiments. Despite not letting the test be my guide, this prepared me for the test anyhow.
I'm glad they work for some people, but flashcards to me seem like they provide a shallow kind of understanding. I don't want to remember the equation, I want to be able to derive it in a pinch, and flash cards don't give me that.
[1] I feel like Anki offers diminishing returns once you get past N3. Advanced words usually have subtle nuances that you can only really pick up through rich context, like in a full paragraph or a TV scene. Native-speaking kids can understand complex words in context because they have a deep grasp of a smaller, simpler vocabulary. That’s why I’m focusing on mastering high-frequency, simple words first to build a learning flywheel. I'm hoping this will eventually let me pick up new words naturally through reading and listening, just like a native kid does.
As for building a learning flywheel. I had a working prototype pre-AI Python project in notebook format that set the foundation for how I thought Kanji learning (or any complex interrelated domain) should build on SRS.
My premise is we should learn by associating what you know with what you should know, based on frequency across the language, not some arbitrary deck… And you shouldn't have to waste effort self reporting, the app should give you similar options to guess from, then if you're wrong, you're wrong.
Do you think that would help you?
> I won’t say LLMs are useless for this. But from my trials, I get about 1 card that’s useful to me out of 10, and even that 1 card still needs rewriting.
I don't know the specifics of how the author tried to do so, but from what I've seen the majority of attempts are, let me drop a chapter of a textbook and say "make flashcards." If that is what we are talking about, then yes, LLMs are useless.
In my mind, though, this is sort of like looking at the very first GitHub Copilot LLM autocomplete from a couple of years ago and concluding, yeah it's nice for one-liners, but it cannot write an app.
If you create a framework around your card-creation AI so that it can use tools, and verify its work to ensure common card-creation pitfalls don't happen, you can get pretty high-quality cards. In my experience, you go from a 10~20% hit rate to a ~90% hit rate, which in my mind is good enough. I got to ~75% quality just from a two extra LLM calls that would assess a potential card against a standard set of rules (adapted from [0]). There are huge Pareto gains to be had here.
I've generated thousdands of cards over the last few months this way. I let the AI add it directly to Anki via AnkiConnect. Then, if when I go to review I find a card that my AI created and I don't like it, I just delete it.
Removing the limitation of card creation is really quite compelling, and I think the area is still highly under-invested in. Would be cool to see a generic framework evolve that one could use. For now, I've been using a personal fork of clanki [1].
[0] https://supermemo.guru/wiki/20_rules_of_knowledge_formulatio...
[1] https://github.com/jasperket/clanki
I'm guessing from all the talk about Anki that people are missing this part. I think these frictionless, digital replacements for note cards are solving the wrong problem. You're never going to spend more time on a given flashcard, and better absorb the information on it, than the first time, when you're sitting there making the thing. Making this step as brief as possible is a bad idea.
I use the Livio English Dictionary to look up words when I read on my tablet and I noticed one day that it keeps a search history, and I got an idea to make an Anki flashcard collection consisting of all the words I've needed to look up while reading. Despite being an obsessive reader my entire life I still regularly encounter words I'm not 100% certain about. Reading itself has spaced repetition built right in, assuming you quiz yourself and then follow up with a dictionary.
Like the author said, understanding the card you're writing in your deck is fundamental. In my case, I would add, this is even true of when you add language cards. For example, I once added the word `thwart`. This card doesn't "cleanly" translate to my native tongue, and I was failing it at all times, I was confusing it with other words such as stifle, stymie etc because have a close meaning but not quite the one in thwart. Only after I grasped the exact definition and usage of it I started to not block on it anymore. I now attempt to be better at it by trying to also recall or make up the antonym of a certain word.
Also I started to create decks for:
1. Emacs commands, including custom shortcut which I use daily, or trying to drill new commands or features that I leant.
2. passages from books I read, mostly for those I use cloze deletions.
3. simple arithmetic, in order to be quicker at doing those without having to use a calculator at all times with me
4. shell commands, for example less frequently used git commands, grep or rg options.
A final note on using LLMs for flashcard creation. Sometimes the LLM can come up with some useful examples, or memory hooks, which help in retaining the information. Yes, I agree here with the author: out of 10 cards created with the LLM you're probably going to retain just one, and even that one will need rewriting.
I use anki in a similar way to the author and it has been truly transformative to my learning and daily habits.
And, like the author, anki has become part of my daily workflow even for things that it's not really specifically designed for; e.g. easy frictionless LaTeX notetaking, cross-referenceable database (via note ids), incremental learning repo, long-term reminders (gtd-style) etc.
I can really recommend them. Now back to flashcards and active recall. They are the secret sauce. People in the thread are saying that understanding is important, while I agree you should understand things its not THAT important.
Important is that you remember not only *facts* what something is. But also how to do something. If you stare at a blank page not being able to do something like writing a a simple typedef struct in C. But knowing what a typedef and struct is, you are missing procedural knowledge.
If you can only programming with an IDE giving you cues like autocompletion you will never form the memory for the actual symbol. Only when you active recall something it will be rememberd until it becomes automatic freeing your working memory from the load and reducing cognitive load overall.
I strongly believe that an AI rephrasing your backside and giving some additional knowledge from your own notes is helpful. You should still write your own notes and flashcards, an AI can help here too but just dont copy and paste them.
Learning can be so much, creating mental models and checking their validity, creating anecdotes, connecting new knowledge and ideas to already learned ones. Have fun!
There are many people that start using anki or flashcards only to stop doing them after a month.
Another interesting observation is that some people use flashcards to optimize for testing not learning. You can get good grades (really good ones) but it might hurt your actual learning. (What that actual means would be a longer topic)
Would definitely take a look!
I am using my own set of flashcards via self-written computer programs, mostly small scripts. The core is simple: one "side" has the question, the other "side" has the answer. I enhanced this on the commandline though, e. g. I can refer to local images (we can show this on the terminal, e. g. I use KDE konsole and then some different commandline programs to show things there. I can even show individual slides of .pdf pages via https://github.com/hzeller/timg, which is pretty cool since I can control which pdf file to show, sometimes manipulating them before showing that).
The author of that blog post at lesleylai, though, is wrong in some regards.
For instance:
> don’t memorize what you don’t understand
I totally understand what he means, e. g. "understand it first before memorizing", and while this is in some ways true, in other ways it is not. I literally had to memorize crap knowledge in order to pass some exams. Some of it was simply boring to no ends, other things were too complicated, but in BOTH cases, being able to memorize it, helped. I may not always understand everything, but being able to connect at the least some parts, did help, just like a spider web that is built up slowly. With that I could lateron learn more, connect more and so forth.
So, while I do agree that understanding is better, sometimes you can not, perhaps you lack time. Even in ALL these cases I had over the years, it still was better to be able to memorize even trivial facts. Of course eventually you have to be picky as to what knowledge you want to store in the brain, since I think it can not store infinite knowledge really (just about everyone forgets stuff eventually), but if your goal is to e. g. pass some exams quickly, then being able to quickly memorize even trivial crap, can be useful. There are a few other things I disagree with too, but for the most part I think this is a very useful blog entry. I am curious what people use else, e. g. other than anki and so forth. Or they may have other learning tricks. I always try to re-align my knowledge when it is for an important topic I care about; topics I once learned but never need again I kind of put into a "storage" preservation mode, e. g. if I ever need it again, I can look it up, but other than that I focus on what seems to be more important to me.
If they help me learn at 100% speed and some other more enjoyable method helps me learn at 25% speed, I’ll pick the latter every time.
Thankfully, I didn’t become a doctor or lawyer, I would have been screwed.
This is moot anyway, because most other learning methods require longer focus and are not possible to do while on the go, during short commute in a tram, or 3 minute wait in a queue, and much more.